Endoscopy evaluation to predict oral appliance outcomes in obstructive sleep apnoea
Bibliographic record
Abstract
The objective of this study was to determine the utility of nasoendoscopy of the upper airway as a predictor of the efficacy of oral appliance treatment in obstructive sleep apnoea (OSA).A total of 61 consecutive patients with moderate-to-severe polysomnographically diagnosed OSA were recruited for this study. Using nasoendoscopy, we prospectively assessed the velopharynx and oro/hypopharynx in each patient while awake and in the supine position. We measured cross-sectional area (CSA), and anteroposterior and lateral diameters of the airway before and after mandibular advancement, and expressed the changes in dimensions as expansion ratios (after/before). We then compared the measurements of responders and nonresponders with oral appliance treatment.The expansion ratio (median (interquartile range)) for the CSA was greater in responders compared with nonresponders in the velopharynx (2.9 (2.3-5.0) versus 1.7 (1.5-1.9), p<0.001) and in the oro/hypopharynx (3.4 (2.5-5.6) versus 2.4 (1.8-3.7), p<0.05). Baseline apnoea-hypopnoea index and the CSA expansion ratio of the velopharynx were independent predictors of oral appliance treatment outcome based on a multivariate logistic regression analysis. The estimated area under the receiver operator characteristic curve was 0.87 and the cut-off value of the expansion ratio was 2.00.These results indicate that nasoendoscopy may have significant clinical utility in predicting the success of oral appliance treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".